Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability

Li, Hongyu; Ju, Ping; Gan, Chun; You, Shutang; Wu, Feng; Liu, Yilu

doi:10.1109/TPWRS.2018.2873410

Title: Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability

Abstract

In this paper, a new systematic method is proposed to analyze the system frequency in power systems under uncertain variability (UV). UV gradually increases in power systems, which originates from the renewable energy generation, random loads, frequency measurement, and communication channels, exerting noteworthy impacts on dynamic system frequency. The UV is modeled as a stochastic process in this paper. Then, the stochastic differential equations are used to describe the dynamic system frequency response (SFR) of a power system under UV, which is based on the SFR model. To assess system frequency dynamics under UV, an index of intra-range probability is put forward. Based on stochastic analysis theory, an analytic method is proposed to analyze the system frequency under UV, by which the intra-range probability can be analytically solved. Compared with Monte Carlo simulation in a typical SFR case and the Iceland electricity transmission network, the proposed method shows almost the same results using much less computation resource. Finally, insights for improving the SFR under UV are provided. The proposed method can be used to quickly verify whether the system frequency could withstand the UV and stay in the security range.

Authors:

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Hohai Univ., Nanjing (China)
Huazhong Univ. of Science and Technology, Wuhan (China)
Univ. of Tennessee, Knoxville, TN (United States)

Publication Date:: Mon Oct 01 00:00:00 EDT 2018

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1523763

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Power Systems

Additional Journal Information:: Journal Volume: 34; Journal Issue: 2; Journal ID: ISSN 0885-8950

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 42 ENGINEERING; stochastic differential equations; system frequency response (SFR); stochastic process; intra-range probability; Monte Carlo simulation

Citation Formats


                    Li, Hongyu, Ju, Ping, Gan, Chun, You, Shutang, Wu, Feng, and Liu, Yilu. Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability.  United States: N. p., 2018. 
Web.  doi:10.1109/TPWRS.2018.2873410.

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                    Li, Hongyu, Ju, Ping, Gan, Chun, You, Shutang, Wu, Feng, & Liu, Yilu. Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability.  United States.  https://doi.org/10.1109/TPWRS.2018.2873410

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                    Li, Hongyu, Ju, Ping, Gan, Chun, You, Shutang, Wu, Feng, and Liu, Yilu. Mon .  
"Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability".  United States.  https://doi.org/10.1109/TPWRS.2018.2873410.  https://www.osti.gov/servlets/purl/1523763.

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@article{osti_1523763,

  title        = {Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability},

  author       = {Li, Hongyu and Ju, Ping and Gan, Chun and You, Shutang and Wu, Feng and Liu, Yilu},

  abstractNote = {In this paper, a new systematic method is proposed to analyze the system frequency in power systems under uncertain variability (UV). UV gradually increases in power systems, which originates from the renewable energy generation, random loads, frequency measurement, and communication channels, exerting noteworthy impacts on dynamic system frequency. The UV is modeled as a stochastic process in this paper. Then, the stochastic differential equations are used to describe the dynamic system frequency response (SFR) of a power system under UV, which is based on the SFR model. To assess system frequency dynamics under UV, an index of intra-range probability is put forward. Based on stochastic analysis theory, an analytic method is proposed to analyze the system frequency under UV, by which the intra-range probability can be analytically solved. Compared with Monte Carlo simulation in a typical SFR case and the Iceland electricity transmission network, the proposed method shows almost the same results using much less computation resource. Finally, insights for improving the SFR under UV are provided. The proposed method can be used to quickly verify whether the system frequency could withstand the UV and stay in the security range.},

  doi          = {10.1109/TPWRS.2018.2873410},

  journal      = {IEEE Transactions on Power Systems},

  number       = 2,

  volume       = 34,

  place        = {United States},

  year         = {Mon Oct 01 00:00:00 EDT 2018},

  month        = {Mon Oct 01 00:00:00 EDT 2018}

}

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Cited by: 16 works

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Fig. 1: The SFR model under uncertain variability.

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Works referencing / citing this record:

Stochastic Control for Intra-Region Probability Maximization of Multi-Machine Power Systems Based on the Quasi-Generalized Hamiltonian Theory
journal, December 2019

Lin, Xue; Sun, Lixia; Ju, Ping
Energies, Vol. 13, Issue 1
DOI: 10.3390/en13010167

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Title: Analytic Analysis for Dynamic System Frequency in Power Systems Under Uncertain Variability

Abstract

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Stochastic Control for Intra-Region Probability Maximization of Multi-Machine Power Systems Based on the Quasi-Generalized Hamiltonian Theory journal, December 2019

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